A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Specifically from Rakuten TV (live.tv.rakuten.co.jp)

FMI: https://cdm-project.com/How-To/ & https://old.reddit.com/r/Piracy/comments/y30ffr/

1. Install Tampermonkey: https://www.tampermonkey.net/
2. Install yt-dlp: https://github.com/yt-dlp/yt-dlp#installation

This is a template for writing product opportunities. These are documents that illuminate some level of strategic thinking related to a particular product pain point that customers have. Typically they are accompanied by research (data, customer conversations, competitive analysis, etc.). This template helps break down the work so that Product Managers can keep moving quickly.

The purpose of filling out this document is to provide enough information for your colleagues to understand the opportunity, research (customer conversations and data), and value of tackling this work. It is not intended to provide solutions, scope or anything necessary to start the project or determine the next steps to start the project. This document focuses squarely on the problem space.